Dan Ariely

If you practice kicking a soccer ball with your eyes closed, it takes only a few tries to become quite good at predicting where the ball will end up. But when “random noise” is added to the situation — a dog chases the ball, a stiff breeze blows through, a neighbor passes by and kicks the ball — the results become quite unpredictable.

If you had to evaluate the kicker’s performance, would you punish him for not predicting that Fluffy would run off with the ball? Would you switch kickers in an attempt to find someone better able to predict Fluffy’s involvement?

That would be absurd. And yet it’s exactly how we reward and punish managers. Managers attempt to make sense of the environment and predict what will result from their decisions.

The problem is that there’s plenty of random noise in competitive strategic decisions. Predicting where the ball will go is equivalent to deciding whether to open a chain of seafood restaurants on the Gulf Coast. The dog running off with the ball is the BP oil spill. When the board reviews the manager’s performance, they’ll focus on the failed restaurants. The stock is down. The chain lost money. Since the manager’s compensation is tied to results, he’ll incur financial penalties. To save face and appear to be taking action, the board may even fire him—thus giving up on someone who may be a good manager but had bad luck.

The oil spill example is an extreme case. In the real world, the random noise is often more subtle and varied—a hundred little things rather than one big thing. But the effect is the same. Rewarding and penalizing leaders based on outcomes overestimates how much variance people actually control. (This works both ways: Just as good managers can suffer from bad outcomes not of their own making, bad managers can be rewarded for good outcomes that occur in spite of their ineptitude.) In fact, the more unpredictable an environment becomes, the more an outcomes-based approach ends up rewarding or penalizing noise.

In the last year I’ve asked many board members how much of a company’s stock value they think should be attributed to the CEO’s strength, and the answer is surprising. They estimate that you’ll get about 10% more stock value, on average, from a good CEO than from a mediocre one. Implicit in that estimate is the understanding that many outcomes are outside a leader’s control.

We can’t entirely avoid outcome-based decisions. Still, we can reduce our reliance on stochastic outcomes. Here are four ways companies can create more sound reward systems.

1. Change the mindset. Publicly recognize that rewarding outcomes is a bad idea, particularly for companies that deal in complex and unpredictable environments.

2. Document crucial assumptions. Analyze a manager’s assumptions at the time when a decision takes place. If they are valid but circumstances change, don’t punish her, but don’t reward her either.

3. Create a standard for good decision making. Making sound assumptions and being explicit about them should be the basic condition for getting a reward. Good decisions are forward-looking, take available information into account, consider all available options, and do not create conflicts of interests.

4. Reward good decisions at the time they’re made. Reinforce smart habits by breaking the link between rewards and outcomes.

Our focus on outcomes is understandable. When a company loses money, people demand that heads roll, even if the changes are more about assuaging shareholders than sound management. Moreover, measuring outcomes is relatively easy to do; decision-based reward systems will be more complex. But as I’ve I said before, “It’s hard” is a terrible reason not to do something. Especially when that something can help reward and retain the people best able to help you grow your business.

This post is based on my column at HBR

What would you think if someone told you: Do the right thing because your life may depend on it. Or more accurately, that you better start making better decisions because it is a matter of life and death. This may sound like something an overprotective parent would tell their child) but in reality it’s the way most of us should start to think about our day to day decisions and their potential to lead to harmful habits and fatal consequences. It is hard to believe that this is true, but recently, researchers have done some interesting analysis on this topic and the results support the idea that personal decisions, and often fairly mundane ones, are a leading cause of premature death in the United States (and I suspect that similar numbers are also the reality in the rest of the developed world).

One of the most interesting analyses on the ways in which our decisions kill us is one by Ralph Keeney (Operation Research, 2008), where Ralph puts forth the claim that 44.5% of all premature deaths in the US result from personal decisions – decisions that involving among others smoking, not exercising, criminality, drug and alcohol use, and unsafe sexual behavior.  In his analysis Ralph carefully defines the nature of both the type of personal decision and what is considered premature death. For instance, dying prematurely in a car accident caused by a drunk driver is not considered premature in this framework because the decision to drive somewhere is not one that can logically be connected to the premature death. Unless, of course, the person who dies is also the drunk driver, in which case this counts as a premature death caused by bad personal decisions.  This is because the decision to drive drunk, and dying as a result, are clearly connected.  In this way you can examine a large set of cases where multiple decision paths are available (the drunk driver also has the option to take a cab, ride with a designated driver, or call a friend), and where these other decision paths are not chosen despite the fact that they won’t directly result in the same negative outcome (i.e fatality). As other types of examples, consider the decisions to smoke (when not smoking is an option), to overeat (when watching our weight is an option), or for people with long term medical conditions to skip taking insulin or asthma medication when these are important to their ongoing health.

Using the same method to examine causes of death in 1900, Keeney finds that during this time only around 10% of premature deaths were caused by personal decisions. Compared to our current 44.5% of premature deaths caused by personal decisions, it seems that on this measure of making decisions that kill ourselves we have “improved” (of course this means that we actually got much worse) dramatically over the years.  And no, this is not because we’ve become a nation of binge-drinking, murderous smokers, it’s largely because the causes of death, like tuberculosis and pneumonia (the most common causes of death in the early 20^th century) are far more rare these days, and the temptation and our ability to make erroneous decisions (think about driving while texting) has increased dramatically.

What this analysis means is that instead of relying on external factors to keep us alive and healthy for longer, we can (and must) learn to rely on our decision-making skills in order to reduce the number of dumb and costly mistakes that we make.

The question then becomes how to help people become better decision-makers. Or at least better at making decisions where their health is concerned. If nearly half of premature deaths in the US can be avoided by making better decisions, it is clear to me that it would be worthwhile to spend much more time and effort to disseminate the knowledge we have gained in social science about the main ways in which people fail to make good decisions.  It is of course over-optimistic to expect that just helping people to see what mistakes they are likely to make will fix the problem, but personally I would be happy even if it only slightly reduced the number of catastrophic decisions.  The next step we need to take is to expand upon the research that examines what kind of methods encourage healthier decision-making and conduct much more research in areas that could help us limit our mistakes. For example, based on research about how people make different decisions when they are sexually aroused we might concentrate on providing comprehensive sexual education that teaches teenagers how to make decisions while in the heat of the moment.  Similarly, by understanding how people think we might be able to teach people to enjoy eating fruit and vegetables; how to make exercise part of their ongoing lifestyle; and develop effective smoking cessation programs. And it would also help to remember, in light of this, that every decision counts.